Advancing crop security: Scientists explore AI and big data to drive “Breeding 4.0”
Scientists in China have found that AI and big data are “revolutionizing crop breeding,” to drive food security and innovation. Methods like high-throughput phenotyping, multi-omics databases, and AI-driven analysis are driving the “Breeding 4.0 era” to overcome the limitations posed by traditional crop breeding methods.
While the EU and US have advanced to Breeding 4.0 by integrating biotechnology, big data, and AI in crop breeding, China is “still in a transition period between stages 2.0 and 3.0,” notes the study. It largely depends on conventional selection and molecular breeding techniques.
“In the context of increasingly complex international situations, accurately identifying core issues in China’s seed industry innovation and seizing the frontier of international seed technology is strategically important,” note the researchers.
The study is published in Engineering and provides a “theoretical basis and practical guidance” for the development of China’s seed industry technology. It was conducted by researchers at the Beijing Academy of Agriculture and Forestry Sciences.
Transitioning from scientific to “intelligent” approaches
According to the scientists, the convergence of biotechnology, big data, and AI aims to advance the “efficient, personalized breeding” of new crop varieties.
The scientists say that identifying core issues in China’s seed industry innovation is “strategically important.”They suggest methods like high-throughput phenotyping, which uses sensors and AI to help crop breeders gather large amounts of data on plant traits faster and automatically. This can help overcome the limitations of slow and limited traditional methods and identify stress- resistance genes in crops.
The study notes that “multi-omics databases” also provide breeders with a clearer view of variation by combining different types of genetic data in crops like maize and soybeans.
AI-based multi-omics analysis is another advancement that can analyze complex genetic regulatory networks to help scientists “better understand” crop traits.
Advanced AI-powered software tools can accelerate crop improvement by combining big data and AI. They offer benefits for breeders, such as optimizing breeding decisions, shortening breeding cycles, and improving selection accuracy.
Advancing the “future of crop breeding”
According to the researchers, China’s seed industry technology development still “lags behind international leaders” in areas like scientific innovation, scientific innovation, core technologies, intelligent breeding systems, germplasm resource utilization, and market competitiveness.
The scientists call for a focus on developing automated intelligent crop phenotype acquisition technology, advancing information fusion mechanisms, and creating omics big data analysis algorithms to overcome these challenges.
“By 2040, China aims to develop frontier core technologies, establish a precision breeding decision system, and transform its seed industry through multidisciplinary integration, data-driven precision breeding, and collaborative innovation platform construction,” notes the study.
The researchers believe that the study provides valuable insights into the “future of crop breeding.”
“As AI and big data technologies continue to evolve, they will likely play an even more significant role in ensuring global food security by enabling more efficient and sustainable crop breeding practices.”
Companies around the world are also turning to AI to advance agriculture. Israel-based BeeHero leverages advanced data analytics, AI, and IoT sensors to improve crop yields, and the Belgian start-up Croptic taps AI and robotics to enhance potato farming.
Meanwhile, US-based Helios AI has developed an AI tool that improves supply chain resilience by predicting the price and availability of agricultural commodities like corn, wheat, and cocoa.
